Skip to content

Instantly share code, notes, and snippets.

@rcrowder

rcrowder/NuPIC_TM_Py_Integration_Tests

Last active August 29, 2015 14:21
Show Gist options
  • Save rcrowder/50b5eddb4a55d98b6f22 to your computer and use it in GitHub Desktop.
Save rcrowder/50b5eddb4a55d98b6f22 to your computer and use it in GitHub Desktop.
Download ZIP
NuPIC C++ TM and Python integration test results
Raw
NuPIC_TM_Py_Integration_Tests
Test: Single sequence
TM: 0.300838s
TP: 3.256973s
TP10X2: 0.051369s
.
----------------------------------------------------------------------
Ran 1 test in 3.842s
OK
FF
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB1
Basic sequence learner. M=1, N=100, P=1.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB11
Like B5, but with activationThreshold = 8 and with each pattern
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 20 | 25 | 2252 | 22.7474747475 | 1.49303727005 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 20 | 25 | 2252 | 22.7474747475 | 1.49303727005 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB3
N=300, M=1, P=1. (See how high we can go with N)
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
FF| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 6879 | 23.0066889632 | 1.40945994315 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 6879 | 23.0066889632 | 1.40945994315 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB4
N=100, M=3, P=1. (See how high we can go with N*M)
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 6833 | 23.0067340067 | 1.41181466433 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 6833 | 23.0067340067 | 1.41181466433 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB5
Like B1 but with cellsPerColumn = 4.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 2273 | 22.9595959596 | 1.3992724799FF4 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB6
Like B4 but with cellsPerColumn = 4.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 6833 | 23.0067340067 | 1.41181466433 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 6833 | 23.0067340067 | 1.41181466433 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB7
Like B1 but with slower learning.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| FF # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB8
Like B7 but with 4 cells per column.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testB9
Like B7 but present the sequence less than 4 times.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 2273 | 22.9595959596 | 1.39927247994 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 .F |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH1
Learn two sequences with a short shared pattern.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 876 | 23.0526315789 | 1.33667632623 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 876 | 23.0526315789 | 1.33667632623 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH2
Same as H1, but with cellsPerColumn == 4, and train multiple times.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 876 | 23.0526315789 | 1.33667632623 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 876 | 23.0526315789 | 1.33667632623 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | NonFFFe | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH3
Like H2, except the shared subsequence is in the beginning.
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 877 | 23.0789473684 | 1.28517004706 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 877 | 23.0789473684 | 1.28517004706 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH4
Shared patterns. Similar to H2 except that patterns are shared between
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 882 | 23.2105263158 | 1.37950972864 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 882 | 23.2105263158 | 1.37950972864 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH5
Combination of H4) and H2).
============FF
======================================================================
FAIL: testB1 (__main__.ExtensiveTemporalMemoryTest)
Basic sequence learner. M=1, N=100, P=1.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 215, in testB1
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 2273 != 0
======================================================================
FAIL: testB11 (__main__.ExtensiveTemporalMemoryTest)
Like B5, but with activationThreshold = 8 and with each pattern
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 357, in testB11
self.assertTrue(unpredictedActiveColumnsMetric.mean < 1)
AssertionError: False is not True
======================================================================
FAIL: testB3 (__main__.ExtensiveTemporalMemoryTest)
N=300, M=1, P=1. (See how high we can go with N)
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 229, in testB3
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 6879 != 0
======================================================================
FAIL: testB4 (__main__.ExtensiveTemporalMemoryTest)
N=100, M=3, P=1. (See how high we can go with N*M)
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 243, in testB4
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 6833 != 0
======================================================================
FAIL: testB5 (__main__.ExtensiveTemporalMemoryTest)
Like B1 but with cellsPerColumn = 4.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 257, in testB5
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 2273 != 0
======================================================================
FAIL: testB6 (__main__.ExtensiveTemporalMemoryTest)
Like B4 but with cellsPerColumn = 4.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 272, in testB6
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 6833 != 0
======================================================================
FAIL: testB7 (__main__.ExtensiveTemporalMemoryTest)
Like B1 but with slower learning.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 301, in testB7
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 2273 != 0
======================================================================
FAIL: testB8 (__main__.ExtensiveTemporalMemoryTest)
Like B7 but with 4 cells per column.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 320, in testB8
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 2273 != 0
======================================================================
FAIL: testH1 (__main__.ExtensiveTemporalMemoryTest)
Learn two sequences with a short shared pattern.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 373, in testH1
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 876 != 0
======================================================================
FAIL: testH2 (__main__.ExtensiveTemporalMemoryTest)
Same as H1, but with cellsPerColumn == 4, and train multiple times.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 399, in testH2
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 876 != 0
======================================================================
FAIL: testH3 (__main__.ExtensiveTemporalMemoryTest)
Like H2, except the shared subsequence is in the beginning.
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 427, in testH3
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 877 != 0
======================================================================
FAIL: testH4 (__main__.ExtensiveTemporalMemoryTest)
Shared patterns. Similar to H2 except that patterns are shared between
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 457, in testH4
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 882 != 0
======================================================================
FAIL: testH5 (__main__.ExtensiveTemporalMemoryTest)
Combination of H4) and H2).
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 482, in testH5
self.assertAllActiveWerePredicted()
File "extensive_temporal_memory_test.py", line 553, in assertAllActiveWerePredicted
self.assertEqual(unpredictedActiveColumnsMetric.sum, 0)
AssertionError: 885 != 0
======================================================================
FAIL: testH9 (__main__.ExtensiveTemporalMemoryTest)
Sensitivity to small amounts of spatial noise during inference
----------------------------------------------------------------------
Traceback (most recent call last):
File "extensive_temporal_memory_test.py", line 506, in testH9
self.assertTrue(unpredictedActiveColumnsMetric.mean < 3)
AssertionError: False is not True
----------------------------------------------------------------------
Ran 15 tests in 0.400s
FAILED (failures=14)
==========================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 885 | 23.2894736842 | 1.35545476418 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 885 | 23.2894736842 | 1.35545476418 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.ExtensiveTemporalMemoryTest.testH9
Sensitivity to small amounts of spatial noise during inference
======================================================
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| Metric | min | max | sum | mean | standard deviation |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
| # active columns | 21 | 25 | 867 | 22.8157894737 | 1.334861774 |
| # predicted => active columns (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive columns (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # unpredicted => active columns (bursting) | 21 | 25 | 867 | 22.8157894737 | 1.334861774 |
| # predicted => active cells (correct) | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => inactive cells (extra) | 0 | 0 | 0 | 0.0 | 0.0 |
| # segments | 0 | 0 | 0 | 0.0 | 0.0 |
| # synapses | 0 | 0 | 0 | 0.0 | 0.0 |
| # predicted => active cells per column for each sequence | None | None | None | None | None |
| # sequences each predicted => active cells appears in | None | None | None | None | None |
+----------------------------------------------------------+------+------+------+---------------+--------------------+
======================================================
Test: __main__.TutorialTemporalMemoryTest.testEndlesslyRepeating
Endlessly repeating sequence of 2 elements
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0][1]
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
Feeding sequence (learning enabled) [50 times]:
[0][1]
+----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 21 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 22 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 23 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 24 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 25 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 26 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 27 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 28 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 29 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 30 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 31 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 32 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 33 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 34 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 35 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 36 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 37 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 38 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 39 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 40 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 41 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 42 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 43 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 44 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 45 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 46 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 47 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 48 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 49 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 50 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 51 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 52 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 53 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 54 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 55 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 56 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 57 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 58 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 59 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 60 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 61 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 62 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 63 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 64 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 65 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 66 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 67 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 68 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 69 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 70 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 71 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 72 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 73 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 74 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 75 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 76 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 77 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 78 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 79 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 80 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 81 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 82 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 83 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 84 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 85 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 86 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 87 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 88 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 89 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 90 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 91 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 92 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 93 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 94 | [0] | . [] | [] | [0] | [] | [] | 0 | 0 | |
| 95 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 96 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 97 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 98 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 99 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
------------------------------------
======================================================
Test: __main__.TutorialTemporalMemoryTest.testEndlesslyRepeatingWithNoNewSynapses
Endlessly repeating sequence of 2 elements with maxNewSynapseCount=1
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0][1]
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1]
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+---+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
Feeding sequence (learning enabled) [100 times]:
[0][1]
+-----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+-----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 21 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 22 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 23 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 24 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 25 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 26 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 27 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 28 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 29 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 30 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 31 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 32 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 33 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 34 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 35 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 36 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 37 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 38 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 39 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 40 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 41 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 42 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 43 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 44 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 45 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 46 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 47 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 48 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 49 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 50 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 51 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 52 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 53 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 54 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 55 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 56 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 57 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 58 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 59 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 60 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 61 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 62 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 63 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 64 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 65 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 66 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 67 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 68 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 69 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 70 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 71 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 72 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 73 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 74 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 75 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 76 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 77 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 78 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 79 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 80 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 81 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 82 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 83 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 84 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 85 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 86 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 87 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 88 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 89 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 90 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 91 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 92 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 93 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 94 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 95 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 96 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 97 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 98 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 99 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 100 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 101 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 102 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 103 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 104 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 105 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 106 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 107 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 108 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 109 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 110 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 111 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 112 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 113 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 114 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 115 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 116 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 117 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 118 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 119 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 120 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 121 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 122 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 123 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 124 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 125 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 126 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 127 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 128 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 129 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 130 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 131 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 132 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 133 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 134 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 135 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 136 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 137 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 138 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 139 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 140 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 141 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 142 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 143 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 144 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 145 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 146 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 147 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 148 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 149 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 150 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 151 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 152 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 153 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 154 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 155 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 156 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 157 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 158 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 159 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 160 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 161 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 162 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 163 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 164 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 165 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 166 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 167 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 168 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 169 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 170 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 171 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 172 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 173 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 174 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 175 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 176 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 177 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 178 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 179 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 180 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 181 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 182 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 183 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 184 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 185 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 186 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 187 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 188 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 189 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 190 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 191 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 192 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 193 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 194 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 195 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 196 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 197 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 198 | [0] | . [] | [] | [0] | [] | [] | 0 | 0 | |
| 199 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
+-----+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 0 / Cell 4 : (0) []
Column 0 / Cell 5 : (0) []
Column 0 / Cell 6 : (0) []
Column 0 / Cell 7 : (0) []
Column 0 / Cell 8 : (0) []
Column 0 / Cell 9 : (0) []
Column 1 / Cell 10 : (0) []
Column 1 / Cell 11 : (0) []
Column 1 / Cell 12 : (0) []
Column 1 / Cell 13 : (0) []
Column 1 / Cell 14 : (0) []
Column 1 / Cell 15 : (0) []
Column 1 / Cell 16 : (0) []
Column 1 / Cell 17 : (0) []
Column 1 / Cell 18 : (0) []
Column 1 / Cell 19 : (0) []
------------------------------------
======================================================
Test: __main__.TutorialTemporalMemoryTest.testFirstOrder
Basic first order sequences
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0][1][2][3]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
Feeding sequence (learning enabled) [2 times]:
[0][1][2][3]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 7 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1][2][3]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] |F 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
======================================================
Test: __main__.TutorialTemporalMemoryTest.testHighOrder
High order sequences (in order)
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled) [5 times]:
[0][1][2][3]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 7 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 11 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 15 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 19 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
Feeding sequence (learning disabled):
[0][1][2][3]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | F [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
======================================================
Test: __main__.TutorialTemporalMemoryTest.testHighOrderAlternating
High order sequences (alternating)
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0][1][2][3]<reset>
[4][1][2][5]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 4 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 7 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
Feeding sequence (learning enabled) [10 times]:
[0][1][2][3]<reset>
[4][1][2][5]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 4 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 7 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 11 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 12 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 15 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 19 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 20 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 21 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 22 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 23 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 24 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 25 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 26 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 27 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 28 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 29 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 30 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 31 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 32 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 33 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 34 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 35 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 36 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 37 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 38 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 39 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 40 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 41 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 42 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 43 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 44 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 45 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 46 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 47 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 48 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 49 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 50 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 51 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 52 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 53 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 54 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 55 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 56 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 57 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 58 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 59 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 60 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 61 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 62 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 63 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 64 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 65 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 66 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 67 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 68 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 69 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 70 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 71 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 72 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 73 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 74 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 75 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 76 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 77 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 78 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 79 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
Column 3 / Cell 12 : (0) []
Column 3 / Cell 13 : (0) []
Column 3 / Cell 14 : (0) []
Column 3 / Cell 15 : (0) []
Column 4 / Cell 16 : (0) []
Column 4 / Cell 17 : (0) []
Column 4 / Cell 18 : (0) []
Column 4 / Cell 19 : (0) []
Column 5 / Cell 20 : (0) []
Column 5 / Cell 21 : (0) []
Column 5 / Cell 22 : (0) []
Column 5 / Cell 23 : (0) []
------------------------------------
Feeding sequence (learning disabled):
[0][1][2][3]<reset>
[4][1][2][5]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 F | 0 | |
| 2 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 3 | [3] | [] | [] | [3] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 4 | [4] | [] | [] | [4] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| 7 | [5] | [] | [] | [5] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
======================================================
Test: __main__.TutorialTemporalMemoryTest.testLongRepeatingWithNovelEnding
Long repeating sequence with novel pattern at the end
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][2]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][2]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][2]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
------------------------------------
Feeding sequence (learning enabled):
[0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][2]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
------------------------------------
Feeding sequence (learning enabled) [10 times]:
[0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][0][1][2]<reset>
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| # | active columns | predicted => active columns (correct) | predicted => inactive columns (extra) | unpredicted => active columns (bursting) | predicted => active cells (correct) | predicted => inactive cells (extra) | # segments | # synapses | sequence labels |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 0 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 1 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 2 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 3 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 4 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 5 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 6 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 7 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 8 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 9 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 10 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 11 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 12 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 13 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 14 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 15 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 16 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 17 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 18 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 19 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 20 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 21 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 22 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 23 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 24 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 25 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 26 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 27 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 28 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 29 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 30 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 31 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 32 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 33 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 34 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 35 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 36 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 37 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 38 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 39 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 40 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 41 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 42 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 43 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 44 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 45 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 46 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 47 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 48 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 49 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 50 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 51 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 52 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 53 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 54 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 55 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 56 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 57 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 58 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 59 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 60 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 61 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 62 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 63 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 64 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 65 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 66 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 67 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 68 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 69 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 70 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 71 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 72 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 73 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 74 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 75 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 76 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 77 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 78 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 79 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 80 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 81 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 82 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 83 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 84 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 85 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 86 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 87 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 88 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 89 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 90 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 91 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 92 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 93 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 94 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 95 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 96 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 97 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 98 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 99 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 100 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 101 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 102 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 103 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 104 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 105 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 106 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 107 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 108 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 109 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 110 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 111 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 112 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 113 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 114 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 115 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 116 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 117 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 118 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 119 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 120 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 121 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 122 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 123 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 124 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 125 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 126 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 127 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 128 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 129 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 130 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 131 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 132 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 133 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 134 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 135 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 136 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 137 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 138 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 139 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 140 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 141 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 142 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 143 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 144 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 145 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 146 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 147 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 148 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 149 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 150 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 151 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 152 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 153 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 154 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 155 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 156 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 157 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 158 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 159 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 160 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 161 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 162 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 163 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 164 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 165 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 166 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 167 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 168 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 169 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 170 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 171 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 172 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 173 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 174 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 175 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 176 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 177 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 178 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 179 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 180 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 181 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 182 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 183 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 184 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 185 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 186 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 187 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 188 | [2] | [] | [] | [2] | [] | [] | 0 | 0 | |
| <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> | <reset> |
| 189 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 190 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 191 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 192 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 193 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 194 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 195 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 196 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 197 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 198 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 199 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 200 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 201 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 202 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 203 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 204 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 205 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 206 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 207 | [0] | [] | [] | [0] | [] | [] | 0 | 0 | |
| 208 | [1] | [] | [] | [1] | [] | [] | 0 | 0 | |
| 209 | [2] | [] | [] | [2] | [] | [] | . 0 | 0 | |
+---------+----------------+---------------------------------------+---------------------------------------+------------------------------------------+-------------------------------------+-------------------------------------+------------+------------+-----------------+
Segments: (format => (#) [(source cell=permanence ...), ...]
------------------------------------
Column 0 / Cell 0 : (0) []
Column 0 / Cell 1 : (0) []
Column 0 / Cell 2 : (0) []
Column 0 / Cell 3 : (0) []
Column 1 / Cell 4 : (0) []
Column 1 / Cell 5 : (0) []
Column 1 / Cell 6 : (0) []
Column 1 / Cell 7 : (0) []
Column 2 / Cell 8 : (0) []
Column 2 / Cell 9 : (0) []
Column 2 / Cell 10 : (0) []
Column 2 / Cell 11 : (0) []
------------------------------------
======================================================
Test: __main__.TutorialTemporalMemoryTest.testSingleEndlesslyRepeating
A single endlessly repeating pattern
======================================================
Initialized new TM with parameters:
{'activationThreshold': 1,
'cellsPerColumn': 4,
'columnDimensions': [6],
'connectedPermanence': 0.5,
'initialPermanence': 0.3,
'maxNewSynapseCount': 6,
'minThreshold': 1,
'permanenceDecrement': 0.05,
'permanenceIncrement': 0.1}
Feeding sequence (learning enabled):
[0]
ERR: Invalid column 1 [/home/nupic/nupic.core/src/nupic/algorithms/TemporalMemory.cpp line 900]
E
======================================================================
ERROR: testSingleEndlesslyRepeating (__main__.TutorialTemporalMemoryTest)
A single endlessly repeating pattern
----------------------------------------------------------------------
Traceback (most recent call last):
File "tutorial_temporal_memory_test.py", line 179, in testSingleEndlesslyRepeating
self.feedTM(sequence)
File "tutorial_temporal_memory_test.py", line 212, in feedTM
sequence, learn=learn, num=num)
File "/home/nupic/nupic/nupic/test/abstract_temporal_memory_test.py", line 77, in feedTM
self.tm.compute(pattern, learn=learn)
File "/home/nupic/nupic/nupic/research/monitor_mixin/temporal_memory_monitor_mixin.py", line 329, in compute
super(TemporalMemoryMonitorMixin, self).compute(activeColumns, True)
File "/home/nupic/nupic/nupic/bindings/algorithms.py", line 4512, in compute
return _algorithms.TemporalMemory_compute(self, *args)
RuntimeError: Invalid column 1
======================================================================
FAIL: testFirstOrder (__main__.TutorialTemporalMemoryTest)
Basic first order sequences
----------------------------------------------------------------------
Traceback (most recent call last):
File "tutorial_temporal_memory_test.py", line 61, in testFirstOrder
self.assertEqual(len(self.tm.mmGetTracePredictedActiveColumns().data[3]), 1)
AssertionError: 0 != 1
======================================================================
FAIL: testHighOrder (__main__.TutorialTemporalMemoryTest)
High order sequences (in order)
----------------------------------------------------------------------
Traceback (most recent call last):
File "tutorial_temporal_memory_test.py", line 79, in testHighOrder
self.assertEqual(len(self.tm.mmGetTracePredictedActiveColumns().data[3]), 1)
AssertionError: 0 != 1
======================================================================
FAIL: testHighOrderAlternating (__main__.TutorialTemporalMemoryTest)
High order sequences (alternating)
----------------------------------------------------------------------
Traceback (most recent call last):
File "tutorial_temporal_memory_test.py", line 125, in testHighOrderAlternating
self.assertEqual(len(self.tm.mmGetTracePredictedActiveColumns().data[3]), 1)
AssertionError: 0 != 1
----------------------------------------------------------------------
Ran 7 tests in 0.234s
FAILED (failures=3, errors=1)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment